Molecular Networks Underlying Resilience to Alzheimer's Disease Among APOE E4 Carriers

APOE E4 携带者对阿尔茨海默病的抵抗力的分子网络

• 批准号: 10188369
• 负责人: Christopher A. Gaiteri
• 金额: $ 76.16万
• 依托单位: YALE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-30 至 2024-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10188369
• 关键词: Affect; Aging; Alleles; Alzheimer' s Disease; Alzheimer' s disease model; Alzheimer' s disease risk; Alzheimer’s disease biomarker; Apolipoprotein E; Bayesian Network; Biological; Biological Markers; Biology; Brain; Brain region; Cerebellum; Clinical; Complex; Consensus; DNA Methylation; Data; Dementia; Development; Disease; Disease susceptibility; Epigenetic Process; Ethnic Origin; Family history of; Future; Gender; Gene Expression; Genes; Genetic; Genetic Determinism; Genetic Predisposition to Disease; Genome; Genomics; Genotype; Goals; Health and Retirement Study; Heterogeneity; Human; Impaired cognition; Incidence; Individual; Intervention; Late Onset Alzheimer Disease; Lead; Longitudinal Studies; Memory; Mendelian randomization; Methods; Methylation; Modeling; Molecular; Multiomic Data; National Institute on Aging; Nature; Neocortex; Nerve Degeneration; Network-based; Pathogenesis; Pathway Analysis; Pathway interactions; Penetrance; Pharmacologic Substance; Pharmacology; Predisposition; Prefrontal Cortex; Prevention therapy; Primary Prevention; Process; Proteins; Proteome; Proteomics; Race; Research; Risk; Risk Factors; Sampling; Secondary Prevention; Statistical Models; System; Systems Biology; Tissue Sample; Tissues; apolipoprotein E-4; base; biological systems; effective therapy; epigenome; epigenomics; genetic signature; genome wide association study; health data; high dimensionality; high risk; high risk population; improved; innovation; multidimensional data; multiple omics; neuropathology; new therapeutic target; novel; polygenic risk score; predictive modeling; prevent; relating to nervous system; religious order study; repaired; resilience; risk prediction; screening; supervised learning; targeted biomarker; therapy development; transcriptome; transcriptome sequencing; transcriptomics

PROJECT SUMMARY/ABSTRACT The e4 allele of the Apolipoprotein E (ApoE) gene has been identified as one of the strongest genetic determinants of late-onset Alzheimer’s disease (AD). In general, the e4 allele is associated with reductions in neural protection and repair, increasing a carrier’s vulnerability to damage accumulated over his/her lifetime. Nevertheless, while the penetrance of ApoE e4 is relatively high, a significant proportion of e4 carriers will never develop AD. The overall goal of this project is to model interactions across multiple omics networks to identify the biological pathways involved in sporadic AD susceptibility versus resilience among high-risk individuals. The multifactorial nature of AD suggests that it may manifest as a result of complex interactions across the genome, epigenome, transcriptome, and proteome. Identifying the central networks involved in AD pathogenesis will require integrative Systems Biology approaches. The proposed research offers a new and innovative way to integrate networks—a dominant feature in biology—across multiple tissues and omics platforms, in order to identify innate and dynamic precursors of resilience to AD, among a high-risk population (e4+). Towards this goal, we will: (1) employ newly developed GWAS-based network analysis, to identify SNP networks that alter the association between ApoE e4 and cognitive decline/dementia; (2) generate DNA methylation and RNA-seq data from brain samples that we will analyze using weighted gene correlation network analysis (WGCNA) to identify networks associated with AD neuropathology and cognitive decline among ApoE e4+; (3) generate proteomic data from brain and CSF samples that we will analyze using WGCNA to identify networks associated with AD neuropathology and cognitive decline among ApoE e4+; (4) use advanced integromic network analysis to identify multi-omics and multi-tissue pathways and biological systems involved in AD resilience. The integration of multiple 'omics' data using systems biology will be crucial for unraveling the connections and interactions between various functional levels involved in complex diseases, such as AD. Overall, our proposed research will improve understanding of the complex biology underlying AD susceptibility. These studies have the potential to identify novel therapeutic targets that could inform the development of future pharmacologic interventions aimed at preventing or slowing AD pathogenesis.

项目摘要/摘要 载脂蛋白E（APOE）基因的E4等位基因已被鉴定为强的遗传之一 晚期阿尔茨海默氏病（AD）的决定因素。通常，E4等位基因与减少 神经保护和维修，增加了载体在其一生中积累的损害的脆弱性。 然而，尽管APOE E4的外观相对较高，但E4载体的很大一部分永远不会 开发广告。该项目的总体目标是建模跨多个OMIC网络的交互以识别 高风险个体中参与零星AD敏感性与韧性有关的生物学途径。 AD的多因素性质表明，它可能是由于跨整个的复杂相互作用而表现出来的 基因组，表观基因组，转录组和蛋白质组。识别参与AD发病机理的中心网络 将需要集成的系统生物学方法。拟议的研究提供了一种新的创新方式 综合网络（生物学中的主要特征）跨越了多个时间和奥米斯平台，以便为了 在高危人群中（E4+）中，确定对AD的弹性的先天和动态前体。走向这个 目标，我们将：（1）员工新开发的基于GWAS的网络分析，以识别改变的SNP网络 ApoE E4与认知能力下降/痴呆之间的关联； （2）产生DNA甲基化和RNA-seq 来自大脑样本的数据我们将使用加权基因相关网络分析（WGCNA）分析到 确定与AD神经病理学相关的网络和APOE E4+的认知下降； （3）生成 来自大脑和CSF样本的蛋白质组学数据，我们将使用WGCNA分析这些数据，以识别关联的网络 APOE E4+的AD神经病理学和认知下降； （4）使用高级整合网分析 确定参与AD弹性的多摩克和多组织途径和生物系统。 使用系统生物学的多个“ OMIC”数据集成对于阐明连接和 涉及复杂疾病的各种功能水平（例如AD）之间的相互作用。总体而言，我们的建议 研究将提高对AD易感性基本生物学的理解。这些研究具有 潜力确定可以告知未来药理发展的新型治疗靶标 旨在防止或减慢AD发病机理的干预措施。